--- title: "VerbaNexAI at ClinicalSkillQA — paper by Tovar et al. (2026)" description: "The paper describes the VerbaNexAI Lab entry to the ClinSkillQA 2026 shared task. 11 references." authors: ["Andrea Menco Tovar", "Jairo E. Serrano", "Edwin Puertas", "Juan Carlos Martinez-Santos"] year: 2026 venue: "Proceedings of the BioNLP 2026 (Shared Tasks)" source: "https://aclanthology.org/2026.bionlp-2.2/" doi: "10.18653/v1/2026.bionlp-2.2" licence: "CC BY 4.0 (ACL Anthology)" licence_url: "https://creativecommons.org/licenses/by/4.0/" summary_licence: "Elamur Cosmic License" canonical: "https://research.elamur.ai/free/en/papers/tovar-2026-verbanexai-clinicalskillqa-visual-evidence-procedural/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/tovar-2026-verbanexai-clinicalskillqa-visual-evidence-procedural/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/47/) / VerbaNexAI at ClinicalSkillQA: From Visual Evidence to Procedural Order A Two-Stage Generative Vision-Language Framework for ClinSkillQA # VerbaNexAI at ClinicalSkillQA: From Visual Evidence to Procedural Order A Two-Stage Generative Vision-Language Framework for ClinSkillQA **Authors:** Andrea Menco Tovar, Jairo E. Serrano, Edwin Puertas and Juan Carlos Martinez-Santos · **Year:** 2026 · **Venue:** [Proceedings of the BioNLP 2026 (Shared Tasks)](https://md.research.elamur.ai/free/en/venues/bionlp/) ([BioNLP 2026](https://md.research.elamur.ai/free/en/venues/bionlp/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/) **Links:** [Publisher's page](https://aclanthology.org/2026.bionlp-2.2/) · [PDF](https://aclanthology.org/2026.bionlp-2.2.pdf) · [DOI 10.18653/v1/2026.bionlp-2.2](https://doi.org/10.18653/v1/2026.bionlp-2.2) · [OpenAlex](https://openalex.org/W7166883534) **Citations:** 0 citations (OpenAlex, 2026-10-14) ## Summary The paper describes the VerbaNexAI Lab entry to the ClinSkillQA 2026 shared task. In this task, shuffled keyframes from videos of students performing clinical procedures must be put back in the correct order and explained. The authors work only on the Basic Life Support (BLS) subset. They use a zero-shot pipeline built on Qwen2-VL-2B-Instruct with no fine-tuning. The pipeline has two stages: - **Stage 1:** The model writes a short factual description of each frame. Deterministic lexical rules turn it into a structured record with entities, actions, a coarse procedural state and uncertainty flags. - **Stage 2:** The same model gives each frame a single ordinal score for its BLS stage. Frames are sorted by that score. Ties are broken by projecting averaged hidden-state embeddings onto one PCA axis. On the test leaderboard the system placed fourth of eight visible teams. Its explanation quality was fairly close to the leader's, but exact sequence reconstruction lagged well behind. The study offers a transparent, reproducible baseline. It also shows that recognising frames one at a time is not enough to separate visually similar neighbouring procedural steps. ## Key points - **Data:** The BLS subset of ClinSkillQA has 200 samples, 150 with four frames and 50 with six, loaded from `BLS_input.json`. A 10-sample DEV subset was used for debugging. - **Ordinal scale (0–5):** approach, prepare, expose_chest, position_hands, compressions, check_or_adjust. If the model's output cannot be parsed, the system retries with a stricter prompt and then falls back to a conservative default score. - **Setup:** Qwen2-VL-2B-Instruct ran in float16 with deterministic decoding (`do_sample=False`) on a Kaggle Tesla T4 GPU. - **Test results:** | Metric | VerbaNexAI Lab | Best visible system | |---|---|---| | Task Accuracy | 0.17 | 0.63 | | Pairwise Micro Accuracy | 0.60 | 0.86 | | BERT F1 | 0.71 | 0.79 | | Overall score | 37.96 | 71.43 | The system ranked 4/8 and produced predictions and rationales for every sample. - **Main weakness:** Temporal discrimination between adjacent, look-alike BLS states. The authors name better temporal modelling and better tie resolution as future work. *Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.* ## Institutions Also on the byline: [Universidad Tecnológica de Bolívar](https://ror.org/01d171k92). 📚 Shelves (6): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [👁️ Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · 2,869 works · [🩺 Medicine](https://md.research.elamur.ai/free/en/shelves/medicine/) · 241 works · [⚙️ Engineering](https://md.research.elamur.ai/free/en/shelves/engineering/) · 133 works · [🩺 Health Informatics](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · 184 works · [⚙️ Control and Systems Engineering](https://md.research.elamur.ai/free/en/shelves/engineering/control-and-systems-engineering/) · 45 works 🧭 Topics (1): [🖼️ Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/) · 657 works ## Cite Cite as: Andrea Menco Tovar, Jairo E. Serrano, Edwin Puertas and Juan Carlos Martinez-Santos. 2026. VerbaNexAI at ClinicalSkillQA: From Visual Evidence to Procedural Order A Two-Stage Generative Vision-Language Framework for ClinSkillQA. Proceedings of the BioNLP 2026 (Shared Tasks). The paper itself, not this page. BibTeX from the library's record of the work. ```bibtex @inproceedings{tovar2026verbanexai, title = {{VerbaNexAI at ClinicalSkillQA: From Visual Evidence to Procedural Order A Two-Stage Generative Vision-Language Framework for ClinSkillQA}}, author = {Andrea Menco Tovar, Jairo E. Serrano, Edwin Puertas and Juan Carlos Martinez-Santos}, booktitle = {Proceedings of the BioNLP 2026 (Shared Tasks)}, year = {2026}, doi = {10.18653/v1/2026.bionlp-2.2}, url = {https://doi.org/10.18653/v1/2026.bionlp-2.2} } ``` - [← previous Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning](https://md.research.elamur.ai/free/en/papers/park-2026-verbal-r3-verbal-reranker-as/) - [next → VERICITE: Evaluating Sentence-Level Citation Faithfulness in Retrieval-Augmented Medical Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-vericite-evaluating-sentence-level-citation/) - [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/47/) ## References 11 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet. 1. For explanation quality, the system obtained BERT Precision = 0.74, BERT Recall = 0.68, and BERT F1 = 0.71. In addition, both Predicted Coverage and Rationale Coverage reached 1.0, showing Rawan AlSaad, Ala Abd-Alrazaq, Sabah Boughorbel, Arfan Ahmed, Marie A. Renault, Rami Damseh, and Javaid Sheikh.… [find](https://scholar.google.com/scholar?q=For+explanation+quality%2C+the+system+obtained+BERT+Precision+%3D+0%2E74%2C+BERT+Recall+%3D+0%2E68%2C+and+BERT+F1+%3D+0%2E71%2E+In+addition%2C+both+Predicted+Coverage+and+Rationale+Coverage+reached+1%2E0%2C+showing+Rawan+AlSaa) 2. Lakshmi Seenivasan, Mobarakol Islam, A. K. Krishna, and Hongliang Ren. 2022. Surgical-VQA: Visual question answering in surgical scenes using transformer. In Lecture Notes in Computer Science, volume 13437, pages 33–43. [find](https://scholar.google.com/scholar?q=Lakshmi+Seenivasan%2C+Mobarakol+Islam%2C+A%2E+K%2E+Krishna%2C+and+Hongliang+Ren%2E+2022%2E+Surgical%2DVQA%3A+Visual+question+answering+in+surgical+scenes+using+transformer%2E+In+Lecture+Notes+in+Computer+Science%2C+volume+) 3. Ian Hartsock and Ghulam Rasool. 2024. 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